Field
Embodiments described herein generally relate to surveillance, more particularly, to analyzing and learning behavior based on a variety of input data.
Description of the Related Art
Many currently available surveillance and monitoring systems (e.g., video surveillance systems, SCADA systems, and the like) are trained to observe specific activities and alert an administrator after detecting those activities. However, such systems require advance knowledge of what actions and/or objects to observe. The activities may be hard-coded into underlying applications or the system may train itself based on provided definitions. In other words, unless the underlying code includes descriptions of certain behaviors, the system is incapable of recognizing such behaviors.
In addition, many surveillance systems, e.g., video surveillance systems, require a significant amount of computing resources, including processor power, storage, and bandwidth. For example, typical video surveillance systems require a large amount of computing resources per camera feed because of the typical size of video data. Given the cost of the resources, such systems are difficult to scale.